• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.131-136
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• 2007

This paper proposes a new approach to eliminate the reflectance component for the detection of text in color images. Color images, printed by color printing technology, normally have an illumination component as well as a reflectance component. It is well known that a reflectance component usually obstructs the task of detecting and recognizing objects like texts in the scene, since it blurs out an overall image. We have developed an approach that efficiently removes reflectance components while preserving illumination components. We decided whether an input image hits Normal or Polarized for determining the light environment, using the histogram which consisted of a red component. We were able to go ahead through the ability to extract by reducing the blur phenomenon of text by light because reflection component by an illumination change and removed it and extracted text. The experimental results have shown a superior performance even when an image has a complex background. Text detection and recognition performance is influenced by changing the illumination condition. Our method is robust to the images with different illumination conditions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.847-852
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• 2010

Text in natural images has a various and important feature of image. Therefore, to detect text and extraction of text, recognizing it is a studied as an important research area. Lately, many applications of various fields is being developed based on mobile phone camera technology. Detecting edge component form gray-scale image and detect an boundary of text regions by local standard deviation and get an connected components using Euclidean distance of RGB color space. Labeling the detected edges and connected component and get bounding boxes each regions. Candidate of text achieved with heuristic rule of text. Detected candidate text regions was merged for generation for one candidate text region, then text region detected with verifying candidate text region using ectilarity characterization of adjacency and ectilarity between candidate text regions. Experctental results, We improved text region detection rate using completentary of edge and color connected component.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.420-438
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• 2004

Artificially or naturally contained texts in the natural images have significant and detailed information about the scenes. If we develop a method that can extract and recognize those texts in real-time, the method can be applied to many important applications. In this paper, we suggest a new method that extracts the text areas in the natural images using the low-level image features of color continuity. gray-level variation and color valiance and that verifies the extracted candidate regions by using the high-level text feature such as stroke. And the two level features are combined hierarchically. The color continuity is used since most of the characters in the same text lesion have the same color, and the gray-level variation is used since the text strokes are distinctive in their gray-values to the background. Also, the color variance is used since the text strokes are distinctive in their gray-values to the background, and this value is more sensitive than the gray-level variations. The text level stroke features are extracted using a multi-resolution wavelet transforms on the local image areas and the feature vectors are input to a SVM(Support Vector Machine) classifier for the verification. We have tested the proposed method using various kinds of the natural images and have confirmed that the extraction rates are very high even in complex background images.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.979-982
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• 2005

This paper is to be pre-processing that decides the text recognizability and quality contained in natural image. Differentiated with the existing studies, In this paper, it suggests the application of partially unified color models, Coiflet Wavelet and text extraction algorithm that uses the closed curve edge features of LoG (laplacian of gaussian)operator. The text image included in natural image such as signboard has the same hue, saturation and value, and there is a certain thickness as for their feature. Each color element is restructured into closed area by LoG operator, the 2nd differential operator. The text area is contracted by Hough Transform, logical AND-OR operator of each color model and Minimum-Distance classifier. This paper targets natural image into which text area is added regardless of the size and resolution of the image, and it is confirmed to have more excellent performance than other algorithms with many restrictions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.2C
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• pp.178-183
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• 2008

The videotext brings important semantic clues into video content analysis. In this paper, we propose an automatic binarization method of text region using a stroke filter. Proposed text binarization method consists of stroke filtering, text color polarity determination, and local region growing. By using the responses of dark and bright stroke filters, we can determine color polarity of text region automatically. And the method is robust against complex background, because it considers stroke information of videotexts by using a stroke filter. The effectiveness of our method is verified by experiments on a challenging database.

• Journal of Broadcast Engineering
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• v.18 no.4
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• pp.559-571
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• 2013

This paper has presented a few problems when the 2D video superimposed the overlay text was converted to the 3D stereoscopic video. To resolve the problems, it proposes the scenario which the original video is divided into two parts, one is the video only with overlay text graphic region and the other is the video with holes, and then processed respectively. And this paper focuses on research only to detect and extract the overlay text graphic region, which is a first step among the processes in the proposed scenario. To decide whether the overlay text is included or not within a frame, it is used the corner density map based on the Harris corner detector. Following that, the overlay text region is extracted using the hybrid method of color and motion information of the overlay text region. The experiment shows the results of the overlay text region detection and extraction process in a few genre video sequence.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5583-5604
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• 2016

In this paper, we present a novel image operator to extract textual information in natural scene images. First, a powerful refiner called the Stroke Color Extension, which extends the widely used Stroke Width Transform by incorporating color information of strokes, is proposed to achieve significantly enhanced performance on intra-character connection and non-character removal. Second, a character classifier is trained by using gradient features. The classifier not only eliminates non-character components but also remains a large number of characters. Third, an effective extractor called the Character Color Transform combines color information of characters and geometry features. It is used to extract potential characters which are not correctly extracted in previous steps. Fourth, a Convolutional Neural Network model is used to verify text candidates, improving the performance of text detection. The proposed technique is tested on two public datasets, i.e., ICDAR2011 dataset and ICDAR2013 dataset. The experimental results show that our approach achieves state-of-the-art performance.

• Science of Emotion and Sensibility
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• v.16 no.4
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• pp.545-556
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• 2013

This study has established the GUI design elements of mobile phones as color, text, layout, graphic icon, and video, under the purpose of exploring the relevance between such elements and brand preference among senior citizens. To accomplish the objective, a model and hypotheses were established, which were tested through a multiple regression analysis. The findings are as follows. First, when the statistical significance was examined by GUI design element of mobile phones, the following results were obtained: Color, text, layout, graphic icon, and video were statistically significant at the significance level given, indicating that such elements all affect brand preference. Second, the relative influence of GUI design elements of mobile phones on brand preference was revealed in the following order: text, color, video, graphic icon, layout. It indicates that boosting the brand preference of senior citizens for mobile phones requires considering 'text' and 'color' first before any other element. In addition, as the influence of 'text' and 'color' becomes greater, the brand preference also becomes higher.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.251-252
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• 2007

The thesis proposed the Text Extraction Algorithm which is a text extraction algorithm which uses the Coiflet Wavelet, YCbCr Color model and the close curve edge feature of adaptive LoG Operator in order to complement the demerit of the existing research which is weak in complexity of background, variety of light and disordered line and similarity of text and background color. This thesis is simulated with natural images which include naturally text area regardless of size, resolution and slant and so on of image. And the proposed algorithm is confirmed to an excellent by compared with an existing extraction algorithm in same image.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.444-447
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• 2007

본 논문에서는 비디오에서 자막을 자동 추출하기 위한 강건한 자막 분리 알고리즘을 제안한다. 주어진 비디오에서 자막이 존재할 가능성이 있는 프레임에 대해 자막 후보 영역의 위치를 찾은 다음, 자막 후보 영역으로부터 강건하게 자막을 추출한다. 추출된 자막 후보 영역에 대해 Dampoint labeling을 수행하여 자막과 비슷한 색상을 갖는 배경을 제거하고, 마지막으로 기하학적 검증을 통해 최종적으로 자막 여부를 판별한다. 제안된 방법을 여러 장르의 비디오에 대해 적용 결과 복잡한 배경을 갖는 비디오에서 자막을 강건하게 추출함을 실험을 통해 확인하였다.